Chuck Hernandez AI Strategy & Applied AI Systems
Engagements

Selected engagements for teams making consequential AI decisions.

I take on a limited number of advisory and hands-on engagements where architecture, delivery discipline, and production judgment all matter.

AI Readiness Assessment

Get a grounded view of what your organization can actually support.

This engagement is for teams that know AI matters but need a grounded assessment of readiness before they commit to a roadmap, a vendor, or a broader rollout.

  • review governance, data realities, architecture, and operating model
  • assess evaluation approach, observability, and release discipline
  • translate technical gaps into executive-level risk and sequencing
  • deliver a scorecard, briefing, and remediation roadmap
AI Due Diligence Support

Assess AI-heavy products, vendors, or technical claims before the commitment becomes expensive.

Designed for leadership teams and operators evaluating AI claims. The focus is not generic market commentary. It is whether the product, architecture, and operating model can support the claims being made.

  • evaluate architecture maturity, control stack, and delivery risk
  • review retrieval and model patterns, governance, and observability
  • highlight issues that could slow integration or break product claims
  • produce severity-ranked findings and a practical 100-day view
Production AI Architecture Review

Review a live or near-live AI system before technical debt turns into operating debt.

Best for teams that already have code, a pilot, or a production launch underway. The review focuses on whether the system is durable, observable, and governable under real operating conditions.

  • assess grounding quality, evals, safeguards, and prompt defense posture
  • review tool use, orchestration, fallback logic, and release controls
  • inspect observability and failure-handling discipline
  • deliver prioritized findings with a stabilization plan
Selected Advisory Support

Senior technical perspective on AI decisions, architecture tradeoffs, and implementation shape.

Best for leadership teams that need an experienced technical counterweight on AI direction, vendor selection, architecture choices, or delivery shape.

  • technology strategy and roadmap challenge sessions
  • vendor evaluation and platform selection support
  • delivery discipline, architecture review, and team assessment
  • leadership briefings and priority-setting for AI initiatives
Embedded AI Engineering

Hands-on support for teams building or stabilizing applied AI systems.

This work fits teams that need a senior AI engineer directly in the codebase on retrieval systems, orchestration layers, eval tooling, or workflow services without overbuilding the engagement around process.

  • build or stabilize hybrid retrieval, reranking, and citation-bound generation
  • design orchestration layers with structured outputs, tool governance, and fail-closed behavior
  • implement eval harnesses, telemetry, regression checks, and drift monitoring
  • work inside an internal engineering team as an embedded senior builder with architecture judgment

See the hiring-focused profile

FAQ

How the engagements are usually structured.

The work is intentionally scoped to move quickly while still producing something durable enough for technical and leadership conversations.

Do these engagements include implementation?

Sometimes. The default shape is assessment, advisory, review, and implementation support when it materially improves the outcome.

Can you work alongside an internal engineering or product team?

Yes. That is often the best arrangement. Internal teams provide context and operating reality, while I provide an outside technical view and help sharpen decision quality.

What does the team usually receive at the end?

Typically a concise briefing, a severity-ranked findings set, and a practical next-step plan. The exact output depends on the engagement type.

Do you also take hands-on build work, or only advisory engagements?

Yes. The default positioning is selective advisory and review work, but I also take embedded AI engineering engagements where the need is a senior builder working directly on retrieval, orchestration, evals, or workflow infrastructure.

Get in touch

If there is a project, architecture question, or role worth discussing, reach out.

The first exchange is usually enough to tell whether the right fit is a readiness review, technical diligence, architecture work, selected advisory support, or embedded engineering help.

Contact View Work
Need proof? See representative work across enterprise AI, modernization, and grounded systems. Hiring instead of buying? Use the dedicated hiring page for staff, principal, or senior AI engineering fit. Need signal? Read the diligence checklist before you commit to a vendor or platform.